The healthcare sector in the U.S. is complex and is also a large sector that generates about 20% of the country's gross domestic product. Healthcare analytics has been used by researchers and practitioners to better understand the industry. In particular, Beta regression models have been proposed to study the utilization of brand name drugs in the U.S. to understand the variability of brand name drug utilization across different areas. Including spatial dependence in Beta regression models can improve their performance. In this talk, we present some empirical results of Beta regression models that are fitted to public datasets obtained from the Medicare & Medicaid Services and  the Internal Revenue Service.